基于自适应马尔可夫参数交互多模型算法的弹道导弹跟踪研究  

Research on Ballistic Missile Tracking Based on Adaptive Markov Parameter IMM

作　　者：封普文[1] 黄长强[1] 曹林平[1] 相猛 任洋[1] 

机构地区：[1]空军工程大学航空航天工程学院,陕西西安710038 [2]西安飞行学院,陕西户县710306

出　　处：《兵工学报》2014年第12期2041-2049,共9页Acta Armamentarii

基　　金：航空科学基金项目(20105196016)

摘　　要：对弹道导弹主动段和自由段进行连续跟踪已成为弹道导弹防御亟待解决的问题。采用多模型交互算法,是解决该问题一条可行途径,但传统交互多模型马尔可夫概率转移矩阵参数固定,切换过程模型概率滞后。文中基于后验信息修正,提出了一种马尔可夫参数值自适应调整算法,根据不匹配模型误差压缩率的变化,自适应调整先验的马尔可夫概率转移矩阵参数,切换过程中较多地压缩不匹配模型的信息,放大匹配模型的信息,提高系统的收敛速度。仿真实验表明:马尔可夫参数自适应调整算法对弹道导弹主动段与自由段交替处的跟踪效果优于传统多模型交互算法。How to consecutively track the boost phase and coast phase transitions without any prior information has become a pressing issue.Solving the problem with interacting multiple model is a feasible method.Since the Markov parameter of conventional interacting multiple model is constant,the model switching slows down.An adaptive Markov parameter IMM （AMP-IMM） algorithm is developed based on the modification of posterior information.The Markov transition probabilities can be modified adaptively in the process of filtering by omitting the information of non-matching model and magnifying the matching model information simultaneously during switching.The algorithm accelerates system convergence speed.Simulation results show that the proposed algorithm can consecutively track BM from the boost phase to the coast phase and is more effective than the conventional interacting multiple model.

关 键 词：兵器科学与技术 弹道导弹 扩展卡尔曼滤波 交互多模型 马尔可夫矩阵 后验信息 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]